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Luoyang, China

Jin G.-H.,China Institute of Technology | Gao X.-Z.,China Institute of Technology | Li X.,China Institute of Technology | Chen Y.-G.,Unit 63880
Yuhang Xuebao/Journal of Astronautics | Year: 2010

The high velocity motion compensation is the key technique for restoring the profile resolution and improving the clarity of ISAR image. The paper proposed a new compensation method based on chirplet transform. The dominant scattering center echo is reconstructed based on windowed rough ISAR image. And the effect of multi-scattering centers on chirp rate is avoided. By chirplet decomposition, the chirp rate is obtained, the velocity is estimated and the phase error is compensated. The experimental result shows that the algorithm is effective. Source

Liu Y.-Q.,Zhengzhou University | Liu C.-C.,Zhengzhou University | Zhao Y.-J.,Zhengzhou University | Zhu J.-D.,Unit 63880
Wuli Xuebao/Acta Physica Sinica | Year: 2015

The existing blind beamforming methods are effective only under the condition that the source signals have some special statistical or structural characteristics. Additionally, the structure of cascade model is complicated and the stability of parallel model is poor when dealing with multi-target signals. To address these problems, a novel blind beamforming algorithm for multi-target signals based on time-frequency (TF) analysis is proposed in this paper. The received array signals are first transformed into time-frequency domain by using quadratic time-frequency distributions (TFDs). Then, the single-source auto-term TF points which show energy concentration at a single signal are extracted through three operations: (i) removing noise points by setting a reasonable threshold, (ii) separating auto-term TF points from cross-term points, and (iii) selecting the single-source auto-term TF points from the auto-term ones. Moreover, these single-source auto-term TF points are classified by the principal eigenvector of their spatial time-frequency distribution matrixes. For each class of TF points, the uncertain set of signal steering vector is given, whose radius is defined as the ultimate range between the center and the elements in the class. Within the uncertain set, an optimization algorithm is provided to get the optimal estimation of the signal steering vector. Finally, the blind beamforming for multi-target signals is achieved based on the Capon method, which can enhance the desired signals and suppress the noise and interference signals. In addition, the influence of parameters selection, the clustering method of unknown source number, and the computational complexity of the proposed algorithm are analyzed. The proposed algorithm can achieve parallel output of multi-target signals under the condition that the array manifold and the direction of arrival (DOA) are unknown. Also, the complex iterative solving processing may be avoided and special limitations on signal characteristics are unnecessary. As a result, it has wide applicability and superior stability compared with the existing blind beamforming methods. Simulations illustrate that the proposed algorithm can well separate multi-target signals which are TF-nondisjoint to a certain extent. It can achieve a higher output signal to interference plus noise ratio (SINR) compared with the constant modulus algorithm (CMA), the independent component analysis (ICA) algorithm, and the joint approximate diagolization of eigenmald (JADE) algorithm. Furthermore, the output performance of the proposed algorithm is close to the optimal Capon beamformer. ©, 2015, Chinese Physical Society. All right reserved. Source

Zhao C.,Capital Normal University | Shi C.,Capital Normal University | Zhao Y.,Yunnan Technician College | Liu Y.,Unit 63880
Applied Mechanics and Materials | Year: 2011

To overcome the shortcomings of the traditional passive-radar-seeker(PRS) for anti-decoy, a complex angle measuring method is proposed in this letter. The complex angle measuring method consists of monopulse angle and spatial spectrum estimation, two angle-measuring units. PRS can get the angle high-resolution features through the complex angle measuring method. So it is possible that PRS confronts decoy. Finally, the simulation results verify the feasibility and anti-decoy capacity of the complex angle-measuring method.© (2011) Trans Tech Publications. Source

Jin G.-H.,China Institute of Technology | Gao X.-Z.,China Institute of Technology | Li X.,China Institute of Technology | Chen Y.-G.,Unit 63880
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2010

The micro-precession dynamics model was improved. And the micro-precession mathematic formulas were set up. The mid-course targets' traits were analyzed from the aspects of target shape, motion specialty and scattering specialty. And the moving scattering center model was raised. In the end, the simulation results provide important foundations to mid-course target recognition. Source

Jin G.-H.,Hunan Institute of Technology | Gao X.-Z.,Hunan Institute of Technology | Li X.,Hunan Institute of Technology | Chen Y.-G.,Unit 63880
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2010

The precession parameters of ballistic targets are of great importance to warheads and decoys discrimination. Based on dynamic ISAR image sequence, this paper analyzes the specialties of scattering and ISAR imaging of spatial ballistic targets. The history of posture changing is deduced. And a method for posture difference evaluating based on image registration is proposed. Moreover, equal interval registration method is adopted to avoid singular registration. Precession parameters are extracted based on posture difference curve. And the extraction process is presented detailedly. Experimental results show that the posture difference can be estimated correctly and the precession parameter estimation has good precision. Source

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